Research on Network Patterns and Influencing Factors of Population Flow and Migration in the Yangtze River Delta Urban Agglomeration, China

Wang, Xuewei; Ding, Shuangli; Cao, Weidong; Fan, Dalong; Tang, Bin

doi:10.3390/su12176803

Cited by 33 publications

(21 citation statements)

References 25 publications

(22 reference statements)

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“…Thus the intensity of the mobility that is carried out will be higher so that it changes the pattern of mobility that is carried out [10]. Overall, the results of this study are very much in line with what Reivenstein said [11] and Wang et all [12], where the distance factor is the main determinant and conditional of people migrating.…”

Section: The Relationship Between Distances Length Of Stay Economic Conditions and Marital Status Of Migrants With The Intensity Of Mobilsupporting

confidence: 84%

Mobility Behavior Analysis of Migrant from Java in South Kuta-Bali

Sarmita¹,

Astawa²

2021

Proceedings of the 2nd International Conference on Law, Social Sciences and Education, ICLSSE 2020, 10 November, Singaraja, Bal

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The purpose of this study was to determine the mobility behavior indicated by the mobility intensity of migrants from Java as well as to prove its relationship with the variables of distance, length of stay, economic conditions, and migrant marital status. To achieve this objective, this study used a survey design with the research subjects being migrants from Java in South Kuta who were taken using snowball sampling techniques. Data analysis was carried out separately, each using quantitative descriptive techniques, product moment correlation, and biserial point correlation by considering the scale of the research data used. The results obtained were the mobility behavior indicated by the intensity of the mobility was very varied and categorized as very strong, the lowest was once a year and the highest reached ten times as far as he knew. Mobility intensity is negatively related (-0.259) and significant at the 1% level (0.009 <0.01) with the distance variable, negatively related (-0.268) and significant at the 1% level (0.007 <0.01) with the length of stay variable, positive correlation (0.508) and significant at the level of 1% (0.000 <0.01) with variable economic conditions, and does not have a significant relationship with the marital status variable of migrants with a correlation value of -0.156 (conversion to a t value of -1.560 is more small from the t table value of 1.987) and a significance value of 0.122 This finding contributed to the development of mobility theories and has implications for input in the formulation of population policy planning.

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Section: The Relationship Between Distances Length Of Stay Economic Conditions and Marital Status Of Migrants With The Intensity Of Mobilsupporting

confidence: 84%

Mobility Behavior Analysis of Migrant from Java in South Kuta-Bali

Sarmita¹,

Astawa²

2021

Proceedings of the 2nd International Conference on Law, Social Sciences and Education, ICLSSE 2020, 10 November, Singaraja, Bal

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“…Compared with previous research results, the results of this paper show that the indicators of public ecology and information infrastructure have a strong ability to explain information flow [ 39 , 40 , 41 ]. For example, PGR, UPD, and CPM of public ecology increased by 1%; meanwhile, the information flow increased by 0.202%, 0.358%, and 0.215%, respectively.…”

Section: Discussioncontrasting

confidence: 69%

“…For example, the urban nodes in the central region of GPUA, such as Xi’an, Xianyang, Baoji, and Weinan, with closer geographical distance and superior location, quickly formed a cohesive subgroup. This feature can be explained in the research of Wu et al [ 40 ]: longer geographic distance will weaken the spread of information flow, while the information flow between neighboring cities has a strong agglomeration. The reason is that due to population migration, convenient transportation, and closer policy cooperation among neighboring cities, the information flow exchanges frequently.…”

Section: Discussionmentioning

confidence: 97%

“…The intercity network is affected by a variety of influencing factors, and identifying the effects and mechanisms of influencing factors plays an important role in effectively improving the coordinated development of cities. Wu explored the spillover effects of the intercity network from four aspects: urban size, economic foundation, major events, and geographic space [ 39 ], while Wang analyzed the influencing factors from the dimensions of economic scale, population scale, infrastructure, urban function positioning, urban event effects, and historical culture [ 40 ]. However, each study does not have a unified standard when constructing the driving factors of the intercity network, which will be adjusted rationally and scientifically according to the focus of the research content.…”

Section: Literature Reviewmentioning

confidence: 99%

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Exploring the Spatiotemporal Evolution and Sustainable Driving Factors of Information Flow Network: A Public Search Attention Perspective

Zhu

Yuen

et al. 2022

IJERPH

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The promotion of information flow reinforces the interactive cooperation and evolutionary process among cities. In the information age, public online search is a typical behavior of Internet society, which is the key to information flow generation and agglomeration. In this study, we attempt to explore the evolutionary characteristics of intercity networks driven by public online social behavior in the information age and construct an information flow network (IFN) from the perspective of public search attention. We also explore the evolution of the IFN in terms of the whole network, node hierarchy, and subgroup aggregation. Meanwhile, we also discuss the impact of the sustainable driving factors on the IFN. Finally, an empirical study was conducted in Guanzhong Plain Urban Agglomeration (GPUA). Our results show that: (1) the information flow in GPUA fluctuating upward in the early study period and gradually decreasing in the later study period. However, the agglomeration degree of information flow in the urban agglomeration continues to increase. (2) The hierarchical structure of urban nodes in GPUA presents a trend of “high in the middle and low on both sides”, and the formation of subgroups is closely related to geographic location. (3) The driving factors all impacting the IFN include public ecology, resource investment, information infrastructure, and economic foundation. This study provides theoretical and practical support for exploring the intercity network and promotes the sustainable urban development.

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“…Scholars' research has mainly revealed the spatial pattern and network characteristics of population mobility at the national level, and has drawn the conclusion that people prefer to be concentrated in major urban agglomerations and regional central cities with a hierarchical pattern [49][50][51], which preliminarily revealed the unbalanced relationship and asymmetrical characteristics of population mobility [6,52]. Meanwhile, population mobility patterns often show spatial differences in different scale units and regions [53].…”

Section: Spatial-temporal Heterogeneity Of Population Mobilitymentioning

confidence: 99%

The Asymmetric Pattern of Population Mobility during the Spring Festival in the Yangtze River Delta Based on Complex Network Analysis: An Empirical Analysis of “Tencent Migration” Big Data

Lin

Yang

et al. 2021

IJGI

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Population mobility patterns are an important reflection of the future distribution of migrant populations and the evolution trends of urbanization patterns. However, although research based on statistical data can reveal the pattern of population flow, it also shows a time lag. Most of the population flow network research based on location services data has failed to fully discuss the symmetry of directional outflows and inflows in the same place and the two-way symmetrical connections between places. This paper creatively proposes and constructs the concept and analysis framework of population flow asymmetry. We used the Yangtze River Delta (YRD) as a typical case and the results of our analysis reveal the temporal and spatial asymmetry of the population flow using complex network analysis methods based on the Spring Festival (SF) population migration big data. We found that the timing asymmetry manifested in such a way that the closer it was to the festival, the greater the scale and intensity of the population movement. This is a feature of the lack of scale and regional differences within China. The spatial asymmetry was manifested in three aspects, network, node, and link, and the core cities with administrative and economic hierarchical advantages dominated the asymmetric pattern of regional population mobility. In addition, distance and administrative boundaries are factors that cannot be ignored in population movements, and they were implicated in the degree of asymmetry by distance enhancement and administrative boundary blocking. The conclusions of this study can not only provide policy decision-making guidelines for population management and resource allocation in the YRD, but they can also provide a reference value for achieving the goal of regional, high-quality, integrated development. Future research will further the discussion and management of socio-economic attributes in order to develop a more detailed and microscopic understanding of the mechanisms of population mobility patterns.

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Research on Network Patterns and Influencing Factors of Population Flow and Migration in the Yangtze River Delta Urban Agglomeration, China

Cited by 33 publications

References 25 publications

Mobility Behavior Analysis of Migrant from Java in South Kuta-Bali

Mobility Behavior Analysis of Migrant from Java in South Kuta-Bali

Exploring the Spatiotemporal Evolution and Sustainable Driving Factors of Information Flow Network: A Public Search Attention Perspective

The Asymmetric Pattern of Population Mobility during the Spring Festival in the Yangtze River Delta Based on Complex Network Analysis: An Empirical Analysis of “Tencent Migration” Big Data

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